1. Computer Vision API for Image Processing Workloads

    Python

    To accomplish image processing workloads with Computer Vision APIs, you may want to use a cloud service provider that offers such capabilities. Different providers like Google Cloud, Azure, and OCI offer different services around computer vision. You can create resources using Pulumi that leverage these services for your image processing tasks.

    For this example, let's focus on using Azure's Cognitive Services, specifically the Computer Vision API. Azure's Cognitive Services provide a variety of pre-trained AI services that include vision, speech, language, and decision-making capabilities.

    The main resource we'll be creating is an Azure Cognitive Services Account, which is the entry point for accessing Azure's Computer Vision API. This account encapsulates the AI services we need and allows us to interact with the Computer Vision API for tasks such as image analysis, object detection, facial recognition, and more.

    Let's write a Pulumi Python program to create an Azure Cognitive Services account tailored for computer vision tasks.

    Here's a step-by-step breakdown of what we're doing in the program:

    1. Import the necessary modules from Pulumi's Azure Native provider.
    2. Create a resource group to organize our Azure resources.
    3. Define the specifications for the Cognitive Services Account, including:
      • The kind of account, which will be ComputerVision to specify that we want to use the Computer Vision API.
      • The SKU name, which represents the pricing tier and performance level. For instance, F0 or S1.
      • The resource's location, which determines where your service instance will be hosted.
    4. Finally, export the endpoint of the Cognitive Services Account so that it can be used by applications to interact with the Computer Vision API.

    Below is the Pulumi program to create this service:

    import pulumi import pulumi_azure_native as azure_native # Initialize a new Pulumi Azure resource group resource_group = azure_native.resources.ResourceGroup("resource_group") # Create the Azure Cognitive Services Account with the kind set to 'ComputerVision'. # This specifies that we want to use the Azure Computer Vision API. cognitive_services_account = azure_native.cognitiveservices.Account("cognitiveServicesAccount", resource_group_name=resource_group.name, kind="ComputerVision", # Specifying the kind of cognitive service we require sku=azure_native.cognitiveservices.SkuArgs( name="S1" # Choose the SKU for your service (S1 represents a standard tier) ), location=resource_group.location, # Align the location with our resource group's location ) # Export the endpoint of the Cognitive Services Account # This can be used by applications to interact with the Computer Vision API pulumi.export("endpoint", cognitive_services_account.endpoint)

    This program will create an Azure Cognitive Services account specifically for computer vision tasks in the resource group we specify. Once your Pulumi program is deployed, it communicates with Azure to provision and configure your resources as defined. After deployment, you will get the endpoint of the Cognitive Services Account as an output, which can then be referenced in your applications to use the Computer Vision API.

    To run this Pulumi program, you will need to have the Pulumi CLI installed, an Azure account, and the appropriate permissions to create resources within your Azure subscription. You would execute the command pulumi up to preview and deploy the resources specified by this program.


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